Post on 18-Jan-2023
THE ROLE OF DAILY CONTRIBUTION COLLECTORS IN THE
GROWTH OF MICRO, SMALL AND MEDIUM ENTERPRISES IN
ZARIA METROPOLIS
By
SAYEDI, Shuaib Ndagi
DEPARTMENT OF BUSINESS ADMINISTRATION,
FACULTY OF MANAGEMENT AND SOCIAL SCIENCES
IBRAHIM BADAMASI BABANGIDA UNIVERSITY, LAPAI.
ABSTRACT
Daily Contribution Collectors (DCCs) or Mobile Collectors (MC) are one of theinformal sources of financing. Informal financial sources have contributedsignificantly to the growth of Micro, Small and Medium Enterprises (MSMEs) inmany developing countries, such as Nigeria. However, they are often faced withproblems of regulation; cost of operations and arbitrary charges onsavings/credits which are unsecured. Therefore, the study examined the roles ofDCCs on the growth of MSMEs in terms of number of employees and annual salesturnover. The study was conducted in Zaria metropolis comprising Zaria andSabon Gari Local Government Areas with population of 17,532 MSMEs operators.Random samples of 391 MSMEs operators who were customers of DCCs areselected from the population using YaroYomens’ formula of determining thesample size. The questionnaire instrument was used to source information fromthe respondents. A set of questionnaires was administered to samples of MSMEsoperators who patronize DCCs. Another set of 13 questionnaires was alsoadministered to DCCs for validity and reliability. Subsequently, the data collectedwere analyzed using descriptive statistics, Pearson product moment correlationcoefficient and t - test statistics to test the hypotheses. The study found that dailyvisits for savings collection is main reason why MSMEs operators saved moneywith DCCs. The correlation coefficient results show that DCCs contributed to thegrowth of MSMEs in terms of increase in number of employees and annual salesturnover. T – test statistic affirms the result by stating that there is significantrelationship between DCCs and MSMEs in terms of number of employees while therelationship was undefined in terms of annual sales turnover. The study therefore,recommended that daily visits for savings collection be encouraged andstrengthened. Moreover, government (at all levels) should search and come outwith sustainable financing ways of assisting MSMEs financing. This is becauseMSMEs have contributed to employment generation and annual sales turnover,therefore, alleviating poverty among the teaming population of Nigeria.Keywords: DCCs, MSMEs, informal sector, Employees and Annual Sales Turnover
1
1.0 Introduction
The rapid growth of informal financial institutions
in recent years in most developing countries is due to
strict conditions attached to loan by formal financial
institutions and inadequate funds made available by
these institutions (Banks and other formal lending
institutions). However, the need to provide funding to
the poor segments of the populations who are
economically active increased the relevance of informal
financial institutions which include Rotational Saving
and Credit Associations (RSCAs), Daily Contribution
Collectors (DCCs) and money lenders, etc.
Daily Contribution scheme which DCCs are the funds
custodian started approximately 50 years ago (1940s)
because of the weaknesses of RSCAs (Seibel, 2001). The
scheme has different names among the three major ethnic
groups in Nigeria. It is called “Ajo” or “susu” among
Yorubas in the West, “Otu” for Igbos in the East and
“Asusu” for Hausas in the North. The DCCs come round on
a daily basis to collect funds from their customers at
home or business premises. The savings collected are
returned at the end of the month (30 days) or as agreed
after deduction of the initial saving or deposit as
commission, translating to 3.33 percent (Ahiawadzi and
Alabi(s), 2007). The financial services provided by the
DCCs have assisted Micro, Small and Medium Enterprises
(MSMEs) to improve their operational efficiency.
2
MSMEs mean different things to different people
because of varying definitions from country to
countries. Even within a country, definitions vary
within different organizational bodies. Srivastava
(2010) states that the definition of MSMEs is based on
five main parameters namely labour, capital, loan size,
fixed assets and annual sales turnover. Ayyagari, Beck
and Demirgue – Kunt (2005) state that the World Bank SME
Department defines micro enterprises as employing up to
10 workers, assets of $10,000 (N1, 500, 000) and annual
sales turnover of $100,000. Small enterprises employ up
to 50 workers, assets and annual sales turnover up to $3
million; and medium enterprises employ up to 300
workers, total assets and annual sales turnover up to
$15 million. Osalor (2010) opines that micro
enterprises employ up to 5 workers, small enterprises
employ from 5 to 19 workers, medium enterprises employ
from 20 to 99 workers, and large enterprises employ 100
workers above.
The definition of MSMEs and Small and Medium
Enterprises (SMES) are similar but different in terms of
broadness. MSMEs are broader in definition relative to
SMEs which shall be used interchangeably in subsequent
discussions. This is because many countries such as
Nigeria and United States of American (U.S.A) etc, do
not create distinction between MSMEs and SMEs sometimes.
In Nigeria, Small and Medium Industries and Equality
3
Investment Scheme (SMIEIS) defines SMEs as any
enterprise with a maximum assets base of N 200m
excluding land and working capital with number of staff
employed not less than 10 or more than 300 (Gunu, 2009).
Irrespective of the nature and composition of MSMEs
and SMEs, informal financial sector which includes DCCs
provides significant percent of informal financial
services to them. CBN (2005) affirms that formal
financial system provided services to about 35 percent
of the economically active population while, the
remaining 65 percent is served by informal financial
sector. The problem of unserved populations by formal
financial system in Nigeria has made Central Bank of
Nigeria (CBN) to come out with microfinance policy. This
policy encourages the establishment of new microfinance
banks and conversion of existing community banks to
microfinance banks after increasing the capitalization
from 5 to 20 million Naira. Consequently, the structures
and services provided by formal financial sector were
increased by decreasing the services of informal
financial sector.
However on 24 September, 2010, CBN recommended
revocation of 224 microfinance banks out of 820 (CBN,
2010). Subsequently, Nigerian Deposit Insurance
Corporation (NDIC) closed 223 microfinance banks (NDIC,
2010). These set backs have increased the activities and
services provided by DCCs and other members of informal
4
financial sector to increase. Oloyede (2008) observes
that “Alajo” or “Ajo” (mobile collectors) appear
prominent among the family members of informal financial
sector. Although, they have problems of regulations,
cost of operation, arbitrary charges on savings and
credits. In spite of that, DCCs and other members of
informal financial sector still contribute to the growth
of MSMEs in terms of number employees and annual sales
turnover in many developing countries which this study
eventually found out.
The main objective of the study is to examine the
role of DCCs to the growth of MSMEs in Nigeria.
Specifically, the study intend to:
i. Examine the role of DCCs on employment generation.
ii. Examine the role of DCCs on the growth of annual
sales turnover of MSMEs.
In line with the above objectives, the
following null hypotheses are stated for testing:
H01: DCCs play no significant role on the growth of
MSMEs’ number of employees.
H02: DCCs play no significant role on the growth of
MSMEs’ annual sales turnover.
2.1 Review of Related Literature
It has been observed over years that MSMEs are
vehicle for poverty alleviation, employment generation
and wealth creation. Nkange (2007) notes that in most
5
developing countries, MSMEs have been used as strategy
for employment generation, food security, poverty
alleviation, rapid industrialization and reversing
rural-urban migration. However, they are faced with
problems of financing, financing sources to choose from
and management capabilities. Aina (2007) identifies that
the rising poverty in Nigeria is due to poorly executed
government programmes toward SMEs to alleviate poverty.
The study suggested more effective and fully funded SMEs
programmes and policies which attract grass root
participation to eradicate poverty. A study conducted by
Onugu (2005) on randomly selected 300 SMEs using
regression as an analytical tool, identified 10 problems
confronting SMEs in Nigeria. These problems are arranged
in order of their magnitude as management, access to
finance, infrastructure, government policy inconsistency
and bureaucracy, environmental factors, multiple taxes
and levies, access to modern technology, unfair
competition, marketing problems and non-availability of
raw materials. The study suggested that promoters of
SMEs should ensure the availability or possession of
management capacity and acumen before pursuing financial
resources for the development of the respective
enterprises.
In addition to the above studies, Gunu (2009)
conducted a study in Ilorin on 50 randomly selected SMEs
using descriptive statistics to present the survey
6
findings. The study found that the major constraint in
sourcing for found from Nigeria Stock Exchange (NSE) is
listing constraint. He suggested that government should
encourage listed SMEs by the way of providing necessary
incentives such as reduction of quotation fee, listing
fee and years of required trading record, etc. A recent
study by Abdullahi, Zakari and Muhammed (2010) in Minna
on randomly selected 540 SMEs using t-test statistic,
identified SMEs have limited credits to use. The limited
credits to SMEs are due to lack of supply as a result of
rationing behaviours of formal and informal financial
institutions. The study concluded that established
formal lending institutions should improve lending terms
and favourable conditions to enable SMEs get access to
credits. So, access to finance is major constrain
confronting MSMEs in Nigeria and financing sources can
be through formal or informal financial institutions.
Formal and informal financial sectors
(institutions) represent interface between demand of
individuals, households and enterprises for financial
services. However, formal financial sector attaches
strict conditions for financial services such as minimum
cash requirement on certain customers’ accounts and
collateral for credits. These make informal financial
sector to be relevance in providing financial services
to MSMEs. Alabi, Alabi and Akorobo (2007) conducted a
study in Ghana on 5 “Susu” clubs and associations; 10
7
mobile collectors; and 5 cooperative using paired
observation test. The study revealed that there is a
relationship between informal financial institutions and
development of MSMEs in terms of turnover on investment
and employment generation. Self regulation was also
identified to be a major set back and recommended a
system of regulating them. In a related study, Oloyede
(2008) investigated Informal Financial Sector, Savings
Mobilization and Rural Development in 16 Local
Government Areas of Ekiti state in Nigeria. The study
sampled 1,100 entrepreneurs and civil servants residing
in rural areas using descriptive statistics as tool for
the analysis. The study found Ajo (Daily Contribution
Scheme) to appear prominent among the family of informal
financial sector, mobilizing savings and channeling
credits to productive investment. It further identified
myriad of problems such as self regulation that still
beset their effective performance. The study suggested
appropriate policy reform by government, harnessing the
much needed rural financing for sustainable economic
development.
Iganiga and Asemotal (2008) also conducted a
similar study in Benin and Ekpoma on 20 informal
financial institutions’ operators, their modus operandi
and the extent of financial intermediation in different
social settings, using descriptive analysis and simple
percentages. The study found mobile collectors and money
8
lenders to be prevalent in semi-urban and urban areas
among entrepreneurs (MSMEs) such as artisans, traders
and skilled workers providing financial services. The
study recommended development of the sector to guarantee
credits and provision of insurance against risks. Yusuf,
Gafar, and Ajaiya (2009) conducted a study in Offa town-
Kwara state on 550 informal sectors (MSMEs and others)
who were members of Rotational Savings and Credits
Associations (RSCAs). The study used p-alpha class
poverty measure and multiple regression analysis. And
found informal financial institutions playing important
role in reducing poverty among people in terms of wealth
creation and employment generation. In a recent related
study by Daniel (2010) on 3,000 SMEs operated by women
using descriptive statistic. The study found informal
financial sector keeping savings and lending to SMEs. It
also identified the sector of lacking strong capital
base and Ajo or susu operators (mobile collectors or
DCCs) are found of absconding with customers’ money. The
study recommended expansion programmes by formal
financial sector to carter for SMEs financing.
From aforementioned studies, many investigations
are conducted on RSCAs and how they affect MSMEs. A
thorough and extensive research conducted has revealed
that the study has never been carried out on the roles
of Daily Contribution Collectors (DCCs) or mobile
collectors to the growth of MSMEs. The DCCs appear
9
prominent among family members of informal financial
sector. This is a gap in the field of academic
discourse. Thus, this study intends to fill the existing
vacuum in order to advance the frontier of knowledge.
3.1 Research Methodology
This study adopts a survey research method using
primary data. The Primary data are unstructured
interviews conducted and two sets of questionnaires
administered to MSMEs operators and DCCs.
The study was conducted in Zaria metropolis of
Kaduna State, Nigeria. The populations of MSMEs in Zaria
metropolis consisting Zaria and Sabon Gari Local
Government Areas (LGAs) are 5,578 and 11,954
respectively (Revenue Office, 2011a and Revenue Office,
2011b). The populations consist of both permanent and
temporary shops of MSMEs operators situated in these
Local Government territories.
The total population of MSMEs in both LGAs is
17,532. Random Samples of 391 MSMEs operators were
selected from the population. The sampled population is
customers who patronize DCCs. This sample size was
determined using Yaro Yamen’s formula as shown below
(Kelechi, 2008 in Ogbadu, 2009).
Therefore,
10
WhereN is the populationn is the sample size 1 is constante is level of significance (i.e. 0.05)
Thus, →
Besides, questionnaire was utilized in sourcing for
data from MSMEs operators who are customers of DCCs.
Another set of questionnaire was also administered to
DCCs in order to ascertain the degree of validity and
reliability of the data source from MSMEs operators.
Based on the sample size, 391 copies of questionnaire
were administered to MSMEs operators and 307 were
returned. Although, 13 copies of questionnaire were
administered to DCCs which all of them were returned and
filled. Out of the returned questionnaire administered
to MSMEs operators, twenty eight (28) respondents who
have joined DCCs as customers for at least five years
were selected for further analysis. Nineteen (19)
respondents (out of 28) provide data relating to annual
sales turnover which were used for the analysis.
The descriptive statistics and Pearson product
moment correlation coefficients were used in this study.
11
The reason is to ascertain whether DCCs have a
relationship with the growth of MSMEs in terms of number
of employees and annual sales turnover. Moreover the
relationship was further tested by using t- test
statistics. T-test statistics is utilized to test the
hypothesis of independent and dependent samples of
variables observed over specific periods of time.
Anyadike (2009) observes that in testing the hypothesis
of correlation between dependent and independent
variables, the following t-test statistics formula is
suggested.
Where, t – is the t – test of significance
r - Is the correlation coefficient
n – Is the sample size
The decision criterion is to accept the hull
hypothesis if the calculated value is less than critical
value (that is, t- test table value) at 0.05 (5%) level
of significance. However, we reject the hull hypothesis
12
n - 21 – r 2
t = r
if the calculated value is more than critical value at
0.05 level of significance.
4.1 Data Presentation and Analysis
Data are presented and analysed in
sections. Section A deals with responses received from
DCCs while section B deals with responses received from
MSMEs.
4.2 Section A : Analysis Relating to DCCs
In this section, data relating to responses
received from DCCs are presented and analyzed below.
Table 4.1: Periods in Business by Daily Contribution
Collectors.
Period (Years) Frequency (F) of
Respondents
Percentage
(%)1 – 5 1 8 6 – 10 3 2311 – 15 5 38
16 & above 4 31TOTAL 13 100
Source: Field Survey (2011).
13
Table 4.1 shows that majority of Daily contribution
collectors have spent more than 10 years in operating
informal financial scheme and carrying depositors or
savers’ risk (MSMEs). Five respondents have spent more
than 10 years in the business representing 38 percent
while four respondents have more than 15 years in the
business representing 31 percent. In addition, three
respondents have spent between six and 10 years in the
business representing 23 percent. The least is one
respondent representing eight percent spending between
one and five years in the business.
Hence, it implies people who are experienced embark
of this business. This is because more than 60 percent
of sampled DCCs have more than 5 years in the business
sustaining informal sector to grow.
Table 4.2: Deposits Constituting Large Accounts of Daily
Contribution Collectors (DCCs)
Amount (N) Frequency (F) of
Respondents
Percentage (%)
50 – 200 4 31210 – 500 4 31510 – 1000 3 231000 and 2 15
14
aboveTOTAL 13 100
Source: Field survey (2011).
Table 4.2 shows that amount of money collected by
DCCs that constitute larger accounts of deposits to them
range from 50 to 500 Naira. Four collectors representing
31 percent respond that 50 to200 Naira are larger
accounts of collections, while another four collectors
representing 31 percent also respond that 210 to 500
Naira are larger account of collections. Three
collectors representing 23 percent respond that 510 to
1000 Naira are the larger accounts, white two (2)
respondents indicate 1000 Naira and above.
Besides the analysis of responses received from
administered questinionaires, interviews were conducted.
A question was asked while interviewing the managing
director of PAT Azeez services on the amount of money
his company charges monthly as commission on daily
savings or deposits. The director replied that the
commission collectable / chargeable is the initial
saving or deposit of the customer. However, if the
customer decided to stop further contributions, the same
initial saving is taken and remainder returned to the
owner. On the question of amount of money charged on a
loan, he replied that 50 Naira is charged for every 1000
Naira per month and no collateral. The loan scheme is
15
designed for customers who have spent three years
contributing money on daily basis.
From the analysis of table 4.3, the sum of 62
percent of DCCs customers contribute between 50 and 500
Naira. This means majority of the customers of DCCs are
low income earners that need financial support to
improve their operational efficiency.
4.3 Section B: Analysis Relating to MSMEs.
In this section, data relating to responses coming
from MSMEs are presented. and analysed .
Table 4.3: Amounts of Money MSMEs Contribute on DailyBasis to DCCs.
Amount (N) Frequency (F) ofRespondents
Percentage (%)
50 – 200 91 30210 – 500 102 33.0510 – 1000 76 25Above 1000 38 12
TOTAL 307 100 Source: Field Survey (2011).
Table 4.3 shows that 102 respondents representing33 percent contribute between 210 and 500 Naira, while91 respondents representing 30 percent contributionranges from 50 to 200 Naira. Seventy Six respondentsrepresenting 25 percent contribute between 510 and 100
16
Naira and 38 respondents representing only 12 percentcontribute 1000 Naira.
On a question relating to commission charged onsavings, all the clients (MSMEs) responded that it isthe initial saving. On risk, they responded that everything one does in life is risky and even formal banksget liquidated and customers loss substantial part oftheir savings.
Hence, it reveals that more than 60 percent of thedeposits on daily basis by MSMEs range from 50 to 500Naira. This goes in line with the information receivedfrom DCCs in table 4.2. This implies that low incomeearners of MSMEs contribute large amount of money toDCCs on daily basis, not minding the risk involved oflosing the money due to insecurity because no insurancecover
Table 4.4: Reasons why MSMEs save money with DCCsReason Frequency (F) of
RespondentsPercentage
(%)Daily visits for savings collection
117 38
Effective and efficient 64 21
17
serviceCharges on savings 49 16Safety and Reliability 77 25
TOTAL 307 100Source: Field Survey (2011).
Table 4.4 indicates that 117 respondents (MSMEs)representing 38 percent saved money with DCCs because oftheir daily visits for savings collection and 77respondents representing 25 percent save money with DCCsbecause of safety and reliability. Sixty fourrespondents representing 21 percent save money becauseof effective and efficient services while 49 respondentsrepresenting 16 percent save money with DCCs because oftheir charges on savings.
Daily visits for savings collection whichconstitutes higher percent of the reasons why MSMEs savetheir DCCs refers to dedicated services being performedby DCCs. They visit their customers on daily basis ( oras agreed) to collect savings or deposits and returnedaccumulated sum at the end of the month. The returnedmoney is reinvented to make the business of MSMEs togrow.
Table 4.5: Descriptive Statistics of Number of Employees of
MSMEs Before and After five years of Joining DCCs as
customers (Paired observation)
Variable Number ofResponden
TotalNumber of
Mean StandardDeviation
18
ts(MSMEs)
Employees
Number of Employees
Before Joining DCCs
28 69 2.4643 1.7420
Number of Employees
After 5 years of
Joining
28 101 3.6071 2.8074
Source: Field Survey (2011).
Table 4.5 indicates an increment in number of
employees, mean and standard deviation after five years
of joining DCCs. This means that DCCs contribute to
employment generation of MSMEs.
Table 4.6: Descriptive Statistics of Annual Sales Turnover of
MSMEs Before and After 5 years of Joining DCCs as Customers
(paired observation)
Variable Number ofRespondents(MSMEs)
Annualsales
TurnoverN
Mean StandardDeviation
Sales Turnover
Before Joining DCCs
19 34,873,00
0
1,835,0
00
53853
Sales Turnover After
5 years of joining
19 46,580,00
0
2,452,0
00
68722
Source: Field Survey (2011).
Table 4.6 shows an increment in annual sales
turnover, mean and standard deviation after five years
19
of Joining DCCs. It means DCCs contribute to sales
growth of MSMEs.
Table 4.7: Results of Pearson Correlation Coefficient and T –
Test of MSMEs
Number Of Employees Before And After 5 Years of
Joining DCCs as
Customers (Paired Observation)
Variable Number of Respondents(MSMEs)
Total Number of Employees
Correlation Result
T-test Result
Number of Employees Before Joining DDCs
28 69 - -
Number of Employees After 5 Years of Joining DDCs
28 101 -1 ≤ r ≤
+ 1
r = 0.70
t0.05(26) = 1.71
t = 5.00
Source: Field Survey (2011).Correlation results can be -1≤ r ≤ +1. If the r =
-1 (Negative Correlation), r= 0 (No relationship
exists) and r= 1(Strong positive relationship). Table
4.7 shows the result of correlation coefficient and
there is relative strong positive correlation between
number of employees before and after five years of MSMES
joining DCCs as customers
20
Furthermore, the t – test statistic shows that
there is significant relationship between number of
employees before and after five years of MSMES joining
DDCs as customers. This is because the t – test
calculated value (5.00) is more than the t – test
critical value (t0.05 = 1.70). So, we reject hull
hypothesis and accept the alternative hypothesis. Type I
error is committed because we reject what ought to be
accepted.
Table 4.8: Results of Pearson Correlation Coefficient and T –
Test of MSMEs Annual
Sales turnover before and after 5 Years of
Joining DCCs as Customers (Paired Observation)
Variable Number ofRespondents(MSMEs)
Annual saleTurnover
N
Correlation
Result
T-test Result
Annual sale
Turnover
Before
Joining DDCs
19 34,873,000 - -
Annual sale
Turnover
After 5
Years of
Joining DDCs
19 46,580,000 -1≤ r ≤
+ 1
r = 1.00
t0.05(17) = 1.74
t =
Source: Field Survey (2011).
21
∞
Table 4.8 shows that there is strong positive
correlation between annual sales turnover before and
after five (5) years of joining DCCs as customers.
The t- test statistic indicates that the relationship is
undefined between annual sales turnover before and after
five (5) years of MSMEs joining DCCs as customers. The
reason is that the t – test statistic (calculated value)
indicates undefined value (∞).
4.3 Findings of the study.
Small amount of deposits or small savings
constitute larger accounts to DCCs. Therefore, majority
of customers are micro and small enterprises. Secondly,
the amount charged as commission on savings is the
initial savings contributed by MSMEs operators. Even, if
the customer seized to continue with the contributions.
Secondly, the amount charged as interest on loan is 50
Naira for every 1,000 Naira borrowed per month without
collateral. Thirdly, DCCs contribute to employment
generation and annual sales turnover of MSMEs. This is
because statistical results show an increment in means
and standard deviations after five years of joining
DCCs. Lastly, correlation results reveal that there is a
positive correlation between DCCs and MSMEs in terms of
number of employees but not annual sales turnover. The t
– test statistic affirms the result that the hull
22
hypothesis should be rejected. This is because there is
a significant relationship between DCCs and MSMEs in
terms of numbers of employees while the relationship is
undefined between DCCs and MSMEs in terms of annual
sales turnover.
5.1 Conclusion and Recommendation
Micro, Small and Medium Enterprises (MSMEs) growth
and survival depend on number of competent employees and
capital. This is because the resources are used to boost
sales which have relationship with profit making of the
organization. To achieve these objectives, MSMEs saved
part of their daily earnings with DCCs. The savings
collected by DCCs is risky because their activities are
not regulated. The amount charged as commission on
savings is significant relative to formal banking
system, because initial saving or deposit is taken as
commission. That is 50 Naira is charged for every 1,000
Naira loan per month.
In addition, there is a positive relationship
between DCCs and MSMEs in terms of number of employees
but not annual sales turnover. T – test statistic
indicates that there is significant relationship between
DCCs and MSMEs in terms of number of employees while the
relationship is undefined in terms of annual sales
turnover.
23
Based on the finding and conclusion, the following
recommendations are made. Firstly, policy makers (CBN
and others) should enact appropriate laws to regulate
the activities of the collectors. Secondly, formal banks
that are regulated and insured by CBN and NDIC
respectively should endeavour to use DCCs as their
agencies in loan disbursement. The reason is that, DCCs
are more familiar and closer to MSMEs operators.
Thirdly, the amount charged as commission on savings
should be reviewed down ward to half of the initial
savings. The reason is that, the present charges are
higher relative to formal bank system charges on savings
or deposits. Daily visits for savings collection should
be encouraged and strengthened. This is because the main
reason why MSMEs save money with DCCs is daily visiting.
Fifthly, government (federal, state and local) should
search for sustainable financing ways to assist MSMEs
financing. The reason is that, they contribute to
employment generation and economic growth, thereby
reducing poverty in Nigeria.
24
References
Abdullahi, H., Zakari, Y.A. and Mohammed, Y. (2010). Formaland Informal Institution
Lending Policies and Access to Credit by Small ScaleEnterprises In Minna: An
empirical assessment. The Lapai journal of Management Science,Volume1 (1):
84-94.
Alabi, G., Alabi, J. and Akorobo, S.T. (2007). The Role of“susu”, A Traditional Informal
Banking System in the Development of Micro and SmallScale Enterprises (MSEs) in Ghana, Journal of InternationalBusiness and Economic Research, volume 6(12): 99 – 116.Retrieved November 15, 2010 from www.cluteinstitute-onlinejournals.com/PDFS/2007222.pdf.
Ahiawadzi, A, Alabi, G. and Alabi, J. (2007). Effects of“susu” – A Traditional Micro-
Finance Mechanism: An Organized and Unorganized Microand Small Enterprise (MSEs) in Ghana, Africa Journal ofBusiness Management, Volume 1(8): 201 – 208. RetrievedNovember 27, 2010, fromwww.academicjournals/PDF/pdf/Nove/Alabi%2001.pdf.
25
Aina, O. (2007). The Role of SMEs in poverty Alleviation inNigeria, Journal of land used
and Development Studies, volume 13(1):124 – 139. RetrievedMarch 20, 2011,
from Journalanduse.org/…/JOURNAL10.pdf.
Anyadike, R.N.C. (2009) Statistical Methods for the Social and EnvironmentalSciences.
Spectrum Book Limited, Ibadan – Oyo State, Nigeria,PP.149
CBN (2005). Microfinance Policy, Regulator and SupervisoryFramework for Nigeria.
Retrieved Dec. 20, 2010, fromwww.cenbank.org/out/publications/gu....
CBN (2010). Two Hundred and Twenty Four (224) Micro FinanceBanks licences are Recommended for Revocation. Sunday Trust,September 26, P. 11 – 12.
Daniel, M. (2010). Enhancing the Capacities of SMEs forPoverty Reduction. Retrieved
March 20, 2010, fromwww.docstoc.com/docs/46146169/there...
Gunu, U. (2009). An Investigation into Small and Medium ScaleEnterprises Funding
and the Nigerian Stock Market: A Study of IlorinMetropolis. Lapai International Journal of Management and SocialScience (LIJOMASS), Volume 2(1): 33 – 45.
Iganiga and Asemotal (2008). The Nigeria Unorganized RuralFinancial Institutions
and Operations. A Frame Work for Improved Rural CreditSchemes in a Fragil Environment, Journal of Social Sciences,Volume 17 (1): 63-71. Retrieved December 10, 2010, fromwww.Krepub;ishers.com/.../jss-17-063-08-531-iganiga-B.o-ab.pdf.
26
NDIC (2010). List of 223 Closed Microfinance Banks as at 24September, 2010.
Sunday Trust, Sept. 26, p. 53 – 55.
Nkanga, E. (2007). Promoting SMEs Via Technology. RetrievedOctober 6, 2010,
from www.thisdayonline.com/nview.php.
Oloyede J.A. (2008). Informal Financial Sector, SavingsMobilization and Rural
Development in Nigeria, Journal of Africa Economic and BusinessReview. Volume 6 (1):44: Retrieved November 30,2010, fromwww.theaebr.com.vol.6No1spring2008Oloyede.pdf.
Ogbadu,E.E.(2009).Profitabilty Through Effective Managementof Material. Journal of
Economics and International Finance, Volume 1(4),pp. 099 –1055.Retrived April 14, 2012, from www.academicjournal.org/jeif/pdf/pdf 2009/sep/ogbadu.pdf,
Onugu, A.N. (2005). Small and Medium Enterprises in Nigeria(SMEs). Unpublished
dissertation, St. clement University, Swiss. RetrievedMarch 20, 2011, fromwww.stclements.edu/grad/gradonug.pdf.
Revenue Office (2011a). Zaria Local Government Area, Kaduna -State, Nigeria.
Revenue Office (2011b). Sabon Gari Local Government Area,Kaduna-State
Nigeria.
Seibel, H.D. (2001). Mainstreaming Informal FinancialInstitutions, Journal of
27
Development Entrepreneurship, volume 6 (1): 83-95. RetrievedDecember 2, 2010, fromwww.microfinancegatewayorg/gm/document-1.9.../250.pdf.
Srivastava, R. (2010). Status of Micro, Small and Medium Enterprises inAfrica.
Retrieved March 20, 2011, fromwww.140online/net/articles/current.
Yusuf N., Gafar, T. and Ajaiya, M.A. (2009). InformalFinancial Institutions and
Poverty Reduction in the Informal Sector of Offa Town,Kwara State: A Case Study of Rotational Saving andCredit Associations (RSCAs), Journal of Social Science, Volume20(1): 71-81. Retrieved November 30, 2010, fromwww.krepublishers.com/.../jss-20-01-071-09-605-Yusuf-N-Tt.pdf.
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